More and more studies focus on variations in homicide rates and crime across cities. These suggest that social, economic and demographic factors explain these variations, such as gross national income per capita, income inequality, corruption, alcohol consumption, cities population size, etc. However, these searches were mainly conducted in North America, and none were interested in these changes across the planet. This thesis will investigate homicide rates, in respect to known predictors, of the largest cities across the world. It will also incorporate data from Numbeo.com about crime perception against person and property as well as the feeling of safety during the day and night. This is done to observe if differences or similarities in the factors linked to homicide rates in cities exist.
This study will focus on the homicide rate, the crime perception against person and property as well as the feeling of safety in 108 cities across the globe. The goal is to identify principle-contributing factors to crime. Bivariate analysis will determine to which degree these three variables share common area and further, which variables form the social, economic and demographic variables can be appropriately integrated into the linear multiple regressions analysis model.
Multivariate analysis results indicate that social income inequalities and corruption are the strongest predictors of homicide rates, crime perception and safety feeling. Corruption emerged stronger on crime perception and feeling of safety than social income inequalities compared to homicide rate. Thus, these results indicate that the same factors are associated with crime in cities as in countries, although some small differences exist.